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Distributed PV Identification Based on High-Precision Bus Data Analysis

机译:基于高精度总线数据分析的分布式光伏辨识

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With the rapid development of distributed photovoltaic (PV), it is necessary to study its low-cost output identification technology. In this paper, a low-cost PV output identification method is proposed by using feature extraction. This paper analyzes the high-precision bus data, and uses harmonic analysis, wavelet analysis and Ensemble Empirical Mode Decomposition (EEMD) to extract the operating features of PV output. Then this paper screens these extracted features with the correlation between features and PV output, the stability of the features at different times and the difference of features in different signals. The appropriate features are selected for PV output identification, and its identification accuracy is calculated. The experimental results show that with the method of the Ensemble Empirical Mode Decomposition, an appropriate operating feature can be extracted. This feature can identify the distributed PV output in small bus bar when the PV is working stably.
机译:随着分布式光伏(PV)的快速发展,有必要研究其低成本输出识别技术。本文采用特征提取提出了一种低成本的PV输出识别方法。本文分析了高精度总线数据,采用谐波分析,小波分析和集合经验模块分解(EEMD)来提取光伏输出的操作特征。然后,本文通过特征和PV输出之间的相关性筛选这些提取的特征,不同时间的特征的稳定性以及不同信号中的特征差异。选择适当的特征进行PV输出识别,并计算其识别精度。实验结果表明,通过集合经验模式分解的方法,可以提取适当的操作特征。当PV稳定地工作时,此功能可以识别小母线中的分布式PV输出。

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